Learn how to review and consider continuous variable distributions in a data set.
- [Narrator] Welcome to chapter four, section six,…where we review continuous variable distributions…and get to see some of R's…very beautiful plotting capabilities.…So, in this section, we are going to review…our continuous variable outcome, which is sleep duration.…We need to see how it relates…to the exposure, alcohol status.…And, as with categorical distributions,…it's best to visualize the distribution…to know what's going on.…So we'll do that, too.…Let's go back to Statistics 101.…
How do we visualize continuous distributions?…Well, I like a histogram any day,…but we can also use box plots.…We are looking for a normal distribution,…but, you know, we might find a skewed one or a bimodal one.…We'll remember our Statistics 101,…and R is so nice to use for graphing.…Let's go do it.…Here is some code I made just for you.…You'll notice I keep putting this read command at the top…just to make sure we are reading in the most recent data set…if we haven't already in the session.…
But since we have, I'll skip that…and go to the next part of the code.…
This detailed, practical course is designed to help those in the field of public health, medicine, and data science to edit, analyze, and interpret data. Learn how to code new variables, use the forward-stepwise modeling process, and document your decisions. Find out how to visualize results by generating charts and graphics, and how to add tables and figures to your documentation. This course helps equip you to independently design, develop, and execute a full BRFSS analysis, and even publish your results in scientific publications or journals.
- Reviewing survey data and documentation
- Conducting a BRFSS analysis
- Understanding naming conventions
- Editing variables
- Reviewing distributions
- Generating an analytic dataset
- Developing descriptive statistics to answer prespecified hypotheses
- Preparing publication-worthy tables and plots
Skill Level Advanced
1. What Is the BRFSS?
2. Designing Your Metadata
3. Reading in Data and Applying Exclusions
4. Preparing for Descriptive Analysis
5. Conducting Descriptive Analysis
Making a frequency macro4m 8s
6. Descriptive Analysis: Weights and Tests
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